decorator VS hy

that doesn't make much sense and there are necessary uses for eval() /exec(), mostly for dynamic creation of code:

For example here's Python dataclasses in the standard library using exec() to create the `__init__` and other methods that go on your dataclass:

https://github.com/python/cpython/blob/main/Lib/dataclasses....

Here's Pydantic using it for a jupyter notebook check:

https://github.com/pydantic/pydantic/blob/594effa279668bd955...

here's Pytest using it to rewrite modules so that functions like assert etc. are instrumented by pytest:

https://github.com/pytest-dev/pytest/blob/eca93db05b6c5ec101...

Here's the decorator module using it (as is the only way to do this in Python) to create a signature matching decorator for an arbitrary function:

https://github.com/micheles/decorator/blob/ad013a2c1ad796996...

All of these libraries are completely secure as eval/exec are used with code fragments that are generated by the libraries, not based on untrusted input.

eval() /exec() are not running executable files, just Python code, the same way all the rest of the package is already doing.

Not exactly the same (doesn't embed into the source like this did), but I believe Hylang[0] is the best Lisp package available for modern Python.

[0] https://github.com/hylang/hy

Isn't that a bit what hy (https://hylang.org/) tries to do ? AIUI it is a lisp interacting directly with the AST of Python, allowing seamless interop: Python modules can be used from hy and vice versa, everything is transparent.

I’ve been keeping loose tabs on this and Hy[1] for a while, but I’ve had some trouble figuring out the major differences between them and the use-cases for either. Would love to see an in-depth comparison in the form of a blog post sometime (though maybe the answer here is to do the research and write one up myself).

1: https://hylang.org

“Python is for scientists. Lisp is for engineers.”

Then what does that make Hy language?

https://hylang.org/

Re Languages with lots of example code and LLM’s

With translators or things like Hy lang, one could get the LLM’s to solve your problem in Python before converting it to another form. Then, you just need a translator. If lacking one, it’s easy to translate by hand.

The practicality of this concept will probably vary by use case. My experiments had GPT doing sketching, implementations, boilerplate, and even porting Python to Rust. A legally-clear LLM trained on multiple languages could probably be fine-tuned to do Python to LISP conversions. If not, Hy might be a stepping stone, too.

You could say so: I've been maintaining the compiler since 2016 ;). Infinitesimal Quest 2 + ε (SQ) exists more to advance Hy than for its own sake.

If you are using Python - you might find Hylang (https://hylang.org) interesting.